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  • MLops
  • MLops
    • Chap 0. Before everything
    • Chap 1. Tools for developers
    • Chap 2. Hardware
    • Chap 3. Infrastructure/platform design
    • Chap 4. Toolkit/codebase
    • Chap 5. Paper reproduction
    • Chap 6. Prototype development
    • Chap 7. Deployment and model serving
    • Chap 8. Productionization/Maintenance/Adoption
    • Chap 9. PR/keep stoa
      • 9.0 Conference
      • 9.1 Challenges/Competitions
      • 9.2 Lectures/Webinars
        • Notes on Stanford MLSys Seminar Series-MLflow
      • 9.3 Tech blogs
      • 9.4 open sources wheels
    • Acknowledge
  • DataOps
    • Chap 0. Preface
    • Chap 1. Data engineering
    • Chap 2. Data integration
    • Chap 3. Data security/privacy
    • Chap 4. Data quality
  • MODELOPS
    • Chap 0. Intro
    • Chap 1. Model registery
  • Fun Facts about Image
    • Chap 0. Preface
    • Chap 1. Process
    • Chap 2. Metrics
    • Chap 3. Case Study
  • Softskills
    • Chap 1. Mindsets
    • Chap 2. Soft skills in getting things done
    • Chap 3. Portfolio and side projects
    • Chap 4. Mentorship
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  2. Chap 9. PR/keep stoa

9.2 Lectures/Webinars

Here is a playlist about ML4healthcare:

  • MIT: Machine Learning for Healthcare (https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-s897-machine-learning-for-healthcare-spring-2019/lecture-videos/arrow-up-right )

  • CS 194-080 Full Stack Deep Learning (UC Berkley Spring 2021) https://docs.google.com/document/d/e/2PACX-1vSSSHcahlrJRvVq4qRKDX2jYLjhgpbWZjqmDcWZ7w3FWItZrlSKw6GY7rcSj5ZkJr6M0DaR8QbKCd8S/pubarrow-up-right

  • CS224n自然语言处理与深度学习笔记汇: https://zhuanlan.zhihu.com/p/31977759

Others:

  • Andrej karpathy: Multi-Task learning in the wilderness:https://slideslive.com/38917690/multitask-learning-in-the-wilderness?ref=library-trendingarrow-up-right

https://cs.uwaterloo.ca/~jorchard/cs473/CS473/Lectures.htmlcs.uwaterloo.cachevron-right

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Last updated 4 years ago